New 
Principal Data Science Manager
 Microsoft | |
 United States, Washington, Redmond | |
 Nov 02, 2025 | |
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OverviewMicrosoft is a company where passionate innovators come to collaborate, envision what can be and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit thinking in a cloud-enabled world.We are seeking a Principal Data Science Manager to build and lead a hybrid team at the intersection of data labeling/annotation operations and applied data science. Your team will deliver high-quality labeled datasets, active-learning loops that directly improve fraud detection precision/recall, reduce false positives, and speed time-to-mitigation across Microsoft businesses. You will be a leader who sets strategy, hires and develops talent, drives cross-org execution, and ships measurable impact. Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
ResponsibilitiesPeople leadership & org health: Hire, lead, and develop a blended team of data scientists, label-ops leads, and analytics engineers; foster an inclusive culture and career growth.Strategy & roadmap: Define the labeling/annotation strategy, taxonomy stewardship, and quality framework aligned to fraud risk priorities and partner roadmaps.Active learning & data quality: Design sampling/uncertainty strategies, gold sets, and label accuracy.Programmatic labeling: Introduce fragile supervision, heuristics, and graph-derived signals to pre-label data.Detection enablement: Partner with engineering and data scientists to integrate labels into feature stores, model training, rules evaluation, and shadow tests.Cross-functional influence: Translate ambiguous fraud patterns into clear label definitions and decision rubrics; align with Product, Engineering, and other stakeholders.Executive communication: Report business impact and influence prioritization decisions.Embody our culture and values. | |